In the predominant sequence-to-function paradigm, 3-D structure is an obligatory prerequisite for protein function. Even though over 100 counter examples can be found in literature, generalization of the functions associated with non-folded (disordered) protein has been mostly ignored. Applying our proprietary bioinformatics software PONDRs on oncogenes, a large fraction of cancer-associated proteins was found to contain large intrinsically disordered regions crucial to function. Thus, a cancer-specific resource database, Cancer DisProtTM and its companion protocol manual will be developed to incorporate functional disordered data for oncogenes. Using PONDRs, disorder/order predictions will be correlated with functions of a representative set of cancer-associated proteins. Data mining these correlations should reveal relationships between disorder/order state and various protein functions, demonstrating the utility of this approach. Ultimately, Cancer DisProt database will be a compendium of hundreds of cancer-associated proteins with experimentally determined regions of disorder correlated with functions. Cancer DisProt will be a useful bioinformatics tool for functional annotation of entire genomes. The database, augmented with methods for studying counter example proteins, will provide the basis for design of novel approaches to the development of cancer treatments and/or drug discovery.